AI Visual Prompt Cookbook

AI Visual Prompt Cookbook

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  Copy a JSON, get a style. Drop one style.json into ChatGPT, Claude, Nano Banana Pro, or any LLM image workflow. Replace the variables, keep the visual system.

  A curated library of plug-and-play visual prompt styles for AI image generation, distilled from visual design references and structured for more consistent, reusable output.

  Curated by @VigoCreativeAI, structured with assistance from OpenAI Codex. Star this repo to follow new style drops.

  🖼️ Browse the online gallery · or jump to the All Styles gallery / full catalog below.

  💬 Made something with a style? Share it in Show and tell · Want a style that isn't here? Request it

Quick Links

| Category | Good for | Start with |
| Photo + Doodle | Social snapshots, lifestyle scenes, playful overlays | Playful Mascot Doodle Snapshot, Cozy Bedroom Doodle Companion |
| Zine + Collage | Fashion posters, music visuals, maximalist editorial layouts | K-pop Apocalypse Ransom Zine, Y2K Grunge Hip-hop Cutout Poster |
| Type Posters | Big headline systems, loud campaign graphics, visual punch | Impact Burst Halftone Comic Poster, Neon Kinetic Typographic Poster |
| Travel + City | Destination posters, street scenes, urban diaries | Clean Triptych Travel Vlog Thumbnail, Tokyo Kawaii Travel Collage Poster |
| Editorial + Minimal | Cleaner compositions, structured layouts, quieter art direction | Tri Color Hardcut Portrait Poster, Soft Analog Future Editorial Poster |
| Product + Campaign | Launch ads, product heroes, retail graphics | Sunlit Coastal Product Blitz, Electric Blue Silhouette Product Launch |

Why This Exists

Most AI image prompts are one-off text blobs: hard to reuse, hard to compare, and hard to iterate on. This repo takes a different approach: each visual style is distilled into a structured style.json you can drop into any LLM-based image generation workflow. Same JSON, more consistent style direction across generations.

Quick Start

1. Browse the Featured Styles, Quick Links, or All Styles.
2. Open a style folder and copy the style.json.
3. Paste the full JSON into ChatGPT, Claude, Nano Banana Pro, or any LLM-based image workflow.
4. Provide your own values for the variables declared in environment_variables, or edit a case in examples[*].values.
5. Generate the final image prompt and send it to your image model.

See the Complete Example below for a full input-to-output walkthrough.

Recommended Image Models

This workflow works best with end-to-end multimodal image models that can read long structured JSON prompts and generate the final image in one step.

- ChatGPT Images 2 (OpenAI, gpt-image-2) — strong text rendering, 2K/4K output, reasoning before generation
- Nano Banana Pro (Google, Gemini 3 Pro Image) — 4K output, multilingual text accuracy, strong subject consistency

Other multimodal LLMs that accept long JSON prompts may also work but are not the primary recommendation.

Complete Example

Input → Output Walkthrough

This example uses Mono Noir Type Portrait Poster Style.

Step 1 — The Style

prompt_template excerpt

text
Create a {ASPECT_RATIO} monochrome editorial p

……（后略，见原文）